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http://bioconductor.org/packages/release/bioc/html/CorMut.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 16,2023. Software package for computing correlated mutations based on selection pressure. Three methods are provided for detecting correlated mutations, including conditional selection pressure, mutual information and Jaccard index. The computation consists of two steps: First, the positive selection sites are detected; second, the mutation correlations are computed among the positive selection sites. Note that the first step is optional. Meanwhile, CorMut facilitates the comparison of the correlated mutations between two conditions by the means of correlated mutation network.

Proper citation: CorMut (RRID:SCR_000053) Copy   

•   Source: SciCrunch Registry

http://microbiology.se/software/megraft/

A software package to graft ribosomal small subunit (16S/18S) fragments onto full-length sequences for accurate species richness and sequencing depth analysis in pyrosequencing-length metagenomes.

Proper citation: Megraft (RRID:SCR_000240) Copy   

•   Source: SciCrunch Registry

http://compbio.cs.utoronto.ca/varid/

Software using a Hidden Markov Model for SNP (single nucleotide polymorphism) and indel identification with AB-SOLiD color-space as well as regular letter-space reads.

Proper citation: VARiD (RRID:SCR_000241) Copy   

•   Source: SciCrunch Registry

http://cistrome.org

Web based integrative platform for transcriptional regulation studies.

Proper citation: Cistrome (RRID:SCR_000242) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.psb.ugent.be/webtools/tapir/

Web server designed for prediction of plant microRNA targets.

Proper citation: TAPIR: target prediction for plant microRNAs (RRID:SCR_000237) Copy   

•   Source: SciCrunch Registry

http://iclab.life.nctu.edu.tw/iclab_webtools/sodock/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. An optimization algorithm based on particle swarm optimization (PSO) for solving flexible protein-ligand docking problems.

Proper citation: SODOCK (RRID:SCR_000193) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/protms/

A software tool for the proteomics community that may help improving analysis of proteomic experimental data.

Proper citation: Quant (RRID:SCR_000267) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/biogrinder/

An open-source bioinformatic tool to create simulated omic shotgun and amplicon sequence libraries for all main sequencing platforms. The tool is available through multiple interfaces like GUI, CLI and API. It is useful for simulating clinical or environmental microbial communities and complements the use of in vitro mock communities.

Proper citation: Grinder (RRID:SCR_000168) Copy   

•   Source: SciCrunch Registry

http://peptideprophet.sourceforge.net/

Software that automatically validates peptide assignments to MS/MS spectra made by database search programs such as SEQUEST.

Proper citation: PeptideProphet (RRID:SCR_000274) Copy   

•   Source: SciCrunch Registry

http://www.cs.toronto.edu/~hilal/rnacontext/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Motif finding software suited for using large-scale RNA-binding affinity datasets to determine the relative binding preferences of RNA-binding proteins (RBPs) for a wide range of RNA sequences and structures. The tool is also implemented in a website.

Proper citation: RNAcontext (RRID:SCR_000179) Copy   

•   Source: SciCrunch Registry

http://www.bioinf.uni-freiburg.de/Software/GraphProt/

Software for modeling binding preferences of RNA-binding proteins from high-throughput experiments such as CLIP-seq and RNAcompete.

Proper citation: GraphProt (RRID:SCR_005842) Copy   

•   Source: SciCrunch Registry

http://www.clipz.unibas.ch/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 20,2019.Database and analysis environment for experimentally determined binding sites of RNA-binding proteins. It supports the automatic functional annotation of short reads resulting primarily from crosslinking and immunoprecipitation experiments (CLIP) performed with RNA-binding proteins in order to identify the binding sites of these proteins. The functional annotation could be also applied to short reads resulting from other types of experiments such as mRNA-Seq, Digital Gene Expression, small RNA cloning, etc. The platform enables visualization and mining of individual data sets as well as analysis involving multiple experimental data sets. The platform can support collaborative projects involving multiple users and groups of users as well as public and private datasets.

Proper citation: CLIPZ (RRID:SCR_005755) Copy   

•   Source: SciCrunch Registry

http://europepmc.org/

Free access to biomedical literature resources including all of PubMed and PubMed Central, agricultural abstracts (from AGRICOLA), over 4 million international life science patents abstracts, National Health Service (NHS) clinical guidelines, and is supplemented with Chinese Biological Abstracts and the Citeseer database. As well as powerful search of abstracts and full text articles, it also includes: * article citations and sort order based on citation count * data citations mined from full text articles * links to and from related databases and institutional repositories * a tool to create bibliographies linked to your ORCID * named entity recognition of keywords and text-mining-based applications showcased in Europe PMC Labs * Tools for recipients of grants from one of the Europe PMC funders to deposit full-text manuscripts and link them to those specific grants. * Web services for programmatic access to all the above bibliographic information and 50,000 grants. * Search by publication date, relevance, or the number of times an article has been cited. * Links to public databases such as UniProt, Protein Data Bank (PDBe), and the European Nucleotide Archive (ENA) are provided. * Through textmining technologies, you can highlight and browse keywords such as gene names, organisms and diseases. * Search 40,000 biomedical research grants awarded to the 18,000 PIs supported by the Europe PMC funders. * Roadtest new tools based on Europe PMC content in Europe PMC labs. * In Europe PMC plus, PIs supported by the Europe PMC funders can link grants to publication information, view article citation and download statistics, and submit manuscripts.

Proper citation: Europe PubMed Central (RRID:SCR_005901) Copy   

•   Source: SciCrunch Registry

http://www-math.u-strasbg.fr/genpred/spip.php?article3

R software package to study, predict and simulate the diffusion of a signal through a temporal gene network. It predicts changes in gene expressions after a biological perturbation in the network and provides graphical outputs that allow monitoring the spread of a signal through the network., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Cascade (RRID:SCR_005861) Copy   

•   Source: SciCrunch Registry

http://www.psb.ugent.be/cbd/papers/BiNGO/Home.html

The Biological Networks Gene Ontology tool (BiNGO) is an open-source Java tool to determine which Gene Ontology (GO) terms are significantly overrepresented in a set of genes. BiNGO can be used either on a list of genes, pasted as text, or interactively on subgraphs of biological networks visualized in Cytoscape. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy, and takes advantage of Cytoscape''''s versatile visualization environment to produce an intuitive and customizable visual representation of the results. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: BiNGO: A Biological Networks Gene Ontology tool (RRID:SCR_005736) Copy   

•   Source: SciCrunch Registry

http://www.nematodes.org/nematodegenomes/index.php/Main_Page

A collaborative wiki that collates information on completed, ongoing and planned genome and transcriptome sequencing projects on species from phylum Nematoda. The intention is to encourage genome sequencing across the diversity of the phylum Nematoda. Wiki includes: * Published complete nematode genomes: A dynamically generated table of all species for which the genome is published. * Nematode species with genomes in progress: A dynamically generated table of all species for which a genome project is underway. Users may add species to the list * Proposed nematode genome projects: To propose a species for genome sequencing, edit its species page, and set the genome project status to proposed. * BLAST server: Search a number of the nematode-genomes-in-progress with genes of your choice. Currently there are 12 draft genomes available... * Genomes with Data available: Genomes with data available for download. Users may add more data URLs to strain pages or update the URLs.

Proper citation: 959 Nematode Genomes (RRID:SCR_006068) Copy   

•   Source: SciCrunch Registry

http://mmdb.iab.keio.ac.jp/

MMMDB, Mouse Multiple tissue Metabolome DataBase, is a freely available metabolomic database containing a collection of metabolites measured from multiple tissues from single mice. The datases are collected using a single instrument and not integrated from literatures, which is useful for capturing the holistic overview of large metabolomic pathway. Currently data from cerabra, cerebella, thymus, spleen, lung, liver, kidney, heart, pancreas, testis, and plasma are provided. Non-targeted analyses were performed by capillary electropherograms time-of-flight mass spectrometry (CE-TOFMS) and, therefore, both identified metabolites and unknown (without matched standard) peaks were uploaded to this database. Not only quantified concentration but also processed raw data such as electropherogram, mass spectrometry, and annotation (such as isotope and fragment) are provided.

Proper citation: MMMDB - Mouse Multiple tissue Metabolome DataBase (RRID:SCR_006064) Copy   

•   Source: SciCrunch Registry

http://biodev.cea.fr/interevol/

InterEvol database is designed for the analysis of co-evolution events at the interface of known structures of hetero- and homo-oligomers. The database can be search and analyzed through 3 interconnected levels of analysis: * From a Keyword or the PDB entry of a complex, you can browse: ** structural homologs for every chain in other complexes ** structural interologs for every interface ** retrieve pre-computed sequence alignments in diverse species * From 1 or 2 sequences of interacting partners: ** build 2 multiple sequence alignments with the same species ordered in each ** query the InterEvol database with alignments using profile-profile comparison method * Visualize structure vs sequence alignment at the complex interface ** A dedicated Pymol plugin is provided ** Alignment views in Pymol are interactively restricted to the residues selected at the interface

Proper citation: InterEvol database (RRID:SCR_006054) Copy   

•   Source: SciCrunch Registry

https://github.com/stamatak/standard-RAxML

Software program for phylogenetic analyses of large datasets under maximum likelihood.

Proper citation: RAxML (RRID:SCR_006086) Copy   

•   Source: SciCrunch Registry

http://ogeedb.embl.de/#summary

Online GEne Essentiality database containing genes that were tested experimentally for essentiality and their features; it also provides a set of tools to systematically explore and analyze these data. The main purpose of this project is to better understand gene essentiality by facilitating the comparisons of the differences and similarities between essential and non-essential genes. This is achieved by collecting not only experimentally tested essential and non-essential genes, but also associated gene features such as expression profiles, duplication status, conservation across species, evolutionary origins and involvement in embryonic development. We focus on large-scale experiments and complement our data with text-mining results. Genes are organized into data sets according to their sources. Genes with variable essentiality status across data sets are tagged as conditionally essential, highlighting the complex interplay between gene functions and environments. Linked tools allow the user to compare gene essentiality among different gene groups, or compare features of essential genes to non-essential genes, and visualize the results. Why is it different from existing databases? * we included both essential and non-essential genes so that we could better understand the gene essentiality by comparing the similarities and differences between the two gene sets; * we compiled a list of features for each gene, including whether they are duplicates or involved in development, the number of other homologous genes in the same genome, as well as their earliest expression stages during development. These features are keys to understand the essentiality of genes; * we also provide a set of tools to explore our data and visualize the results. For example, users can simply divide genes into two groups according to whether they are duplicates, calculate the proportion of essential genes (PE%) in each group and then visualize the results in a bar plot; or they can classify genes into multiple groups according to their earliest expression stages during evolution, compare the essentiality of genes that were expressed earlier with those were latter, and plot the results in a line chart.

Proper citation: OGEE - Online GEne Essentiality database (RRID:SCR_006080) Copy   

•   Source: SciCrunch Registry